Seo backlinks

Backlink / Off-Page SEO Audit

Off-page SEO is the part of ranking you do not fully control: who links to a site, with what anchor text, and how trustworthy those sources are. This skill is an audit + acquisition methodology, not a vendor wrapper. Backlink discovery needs a crawl of the web's link graph, which no public crawler gives in full — so the metrics here depend on a backlink data source (a backlink API, search-console link export, or an open web-graph dataset). See the seo-rank-data skill for sourcing that data and its confidence weighting. Everything below is the analysis you run on top of that data.

When to use

• Auditing why a site under- or over-performs vs. its link profile.
• Vetting a domain before purchase (expired/aged domain heritage risk).
• Detecting toxic links and deciding whether to disavow.
• Finding link-building opportunities (competitor gap, digital PR).
• Checking exposure to parasite-SEO / negative-SEO patterns.

Data sources and confidence

You will almost never have a complete link graph. Label every metric with its source and a confidence weight, and never present an inferred number as a measured fact.

Source	What it gives	Confidence	Freshness
Commercial backlink API (e.g. a SaaS index)	Backlinks, referring domains, authority, anchors, follow ratio, velocity	1.0	days–weeks
Search Console link export (own site only)	Top linking sites + anchors (sampled, no authority)	0.85	~days
Open web-graph dataset (e.g. Common Crawl)	Domain-level in-degree, harmonic centrality, top referrers (no authority scores)	0.5	quarterly
Live verification crawl (your own crawler)	Whether a known backlink still exists, follow/nofollow, anchor	0.95	real-time

Data sufficiency gate (falsifiability): of the 7 scored factors below, count how many have at least one source. If fewer than 4 are covered, do not emit a numeric 0–100 score — emit INSUFFICIENT DATA (X/7 factors) plus the factor scores you do have. A confident number built on one weak source reads as "poor health" when the truth is "we lack data". When only an open web-graph dataset is available, cap the score at 70/100.

Audit framework (produce all 7 sections)

1. Profile overview

Pull totals: backlinks, referring domains, follow ratio, authority/rank, trend.

Metric	Good	Warning	Critical
Referring domains	>100	20–100	<20
Follow ratio	>60%	40–60%	<40%
Single-domain concentration	no domain >5% of links	one domain >10%	one domain >25%
Trend	growing or stable	slow decline	rapid decline (>20%/quarter)

2. Anchor-text distribution

Over-optimized anchors are the classic algorithmic-penalty (Penguin-lineage) signal.

Anchor type	Healthy range	Over-optimization flag
Branded (company/domain)	30–50%	<15% (looks built, not earned)
Naked URL	15–25%	—
Generic ("click here", "read more")	10–20%	—
Exact-match keyword	3–10%	>15%
Partial-match keyword	5–15%	>25%
Long-tail / natural sentence	5–15%	—

Flag exact-match anchors over 15%, especially when concentrated from few domains — that is a manipulation fingerprint, not natural editorial linking.

3. Referring-domain quality

• TLD mix: .edu/.gov/.org skew authoritative; a flood of cheap .xyz/.top/.info skews spam.
• Geo mix: should roughly match the target market; 80%+ from irrelevant countries is a PBN tell.
• Authority spread: healthy profiles have links across all authority tiers, not only the top.
• Per-domain follow/nofollow: domains that only nofollow pass branding but little ranking value.

4. Toxic-link detection

High-risk patterns (flag immediately, candidates for disavow):

• Private Blog Network (PBN) footprints: shared hosting/IP, identical themes, thin reciprocal money sites.
• 100% exact-match anchors from a single domain.
• Links from penalized or deindexed domains.
• Mass directory dumps (50+ low-quality directory links).
• Link farms / pages with 10k+ outbound links.
• Sitewide footer/sidebar links across an entire domain (paid-link footprint).

Medium-risk (review manually before acting):

• Links from unrelated niches; reciprocal A↔B patterns; links from thin pages (<100 words);

  50 backlinks all from one domain.

5. Expired / aged-domain heritage risk

Before buying or migrating onto an aged domain, audit its past life — Google carries history forward, and a domain can arrive pre-penalized.

• Pull historical snapshots (web archive) for prior content: was it a real site, or a spam/PBN/adult/gambling flip?
• Check the existing backlink profile against sections 2–4 before relaunch.
• Confirm it was not previously deindexed; verify a clean reindex after relaunch.
• A domain with strong raw metrics but a toxic anchor profile or off-niche history is a liability, not a shortcut.

6. Parasite-SEO / negative-SEO exposure

• Parasite SEO (inbound risk): spam pages hosted on a high-authority host (UGC subdomains, open profile/forum pages, abandoned subfolders) can borrow your authority. Audit subdomains and user-generated areas for content you did not publish.
• Negative SEO: a sudden spike of toxic links pointed at you. The defense is the velocity baseline in section 7 — without it you cannot tell an attack from organic growth.

7. Link velocity & gap

• New/lost links over 30/60/90 days (needs a time-series source). Watch for: unexplained spikes (possible negative-SEO injection), mass losses (penalty or content removal), and steadily declining velocity (content no longer earning links).
• Competitor gap: domains linking to a competitor but not to the target = the prioritized acquisition list; domains linking to both = relationships to deepen.

Backlink health score (0–100)

Factor	Weight	Preferred source order
Referring-domain count	20%	API > web-graph in-degree
Domain-quality distribution	20%	API authority > web-graph centrality
Anchor-text naturalness	15%	API > Search Console anchors
Toxic-link ratio	20%	API spam signals > verification crawl
Link-velocity trend	10%	API time-series only
Follow/nofollow ratio	5%	API > verification crawl
Geographic relevance	10%	API country data

Score each factor 0–100, weight, sum. Redistribute the weight of any unsourced factor proportionally across the rest. Always print which factors were scored vs. skipped, with their source and confidence — apply the sufficiency gate from above before showing a number.

Falsifiability check (run before delivering)

State, for every material claim, how you would know it was wrong and the leading indicator to watch.

Claim	How would we know it's wrong?	Leading indicator
"This link is toxic / disavow it"	Disavowing a borderline link drops a ranking it was actually helping	Track rankings 4–8 weeks post-disavow; disavow conservatively, in batches
"We have a toxic-anchor problem"	The over-optimized anchors come from scraper copies of one real editorial link, not built links	Group anchors by root domain, not by raw count
"Link removed"	The page is JS-rendered and the <a> exists post-hydration	Mark unverifiable_js instead of removed when the source is an SPA shell
"Negative-SEO attack"	The spike is a legitimate viral/PR event	Compare against the velocity baseline + check anchor/topic relevance of new links
"This aged domain is safe to buy"	Post-relaunch it fails to index or rankings never materialize	Verify reindex + run a fresh profile audit 30 days after relaunch
"Referring-domain count = N"	N counts links, or counts duplicate subdomains as distinct	Deduplicate to registrable domains; reconcile summary vs. the verified link list

If any check fails, fix the finding before reporting. Distinguish "not crawled" vs. "below threshold" vs. "error" — never collapse them into "not found".

Disavow guidance

Disavow is a last resort, scoped to manipulative links you cannot get removed.

1. Attempt manual removal first (outreach to the linking site).
2. Disavow at domain level (domain:example.com) for whole-domain spam; per-URL only for surgical cases.
3. Keep it conservative — disavowing healthy links removes ranking signal. Re-measure after 4–8 weeks.
4. Google's own guidance: most sites never need a disavow file; the algorithm ignores most spam automatically.

Link earning (digital PR — the durable strategy)

The only links that survive algorithm updates are editorially earned. Prioritize creating link-worthy assets over chasing volume:

• Original data / research: surveys, benchmarks, "state of X" reports — journalists cite primary data.
• Free tools & calculators: a small Next.js utility page earns links passively for years.
• Expert commentary / reactive PR: respond to journalist requests in your niche.
• Genuinely useful long-form that becomes the canonical reference for a query.

For our stack, ship link-bait assets as fast, indexable RSC routes:

// app/[locale]/tools/roi-calculator/page.tsx — a linkable free-tool page (RSC + client island)
import type { Metadata } from "next";
import { getTranslations } from "next-intl/server";
import { Calculator } from "./calculator"; // "use client" island for interactivity

export async function generateMetadata(
  { params }: { params: Promise<{ locale: string }> },
): Promise<Metadata> {
  const { locale } = await params;
  const t = await getTranslations({ locale, namespace: "roiTool" });
  const url = `${process.env.NEXT_PUBLIC_SITE_URL}/${locale}/tools/roi-calculator`;
  return {
    title: t("title"),
    description: t("description"),
    alternates: { canonical: url }, // stable canonical = links consolidate to one URL
    openGraph: { url, title: t("title"), description: t("description") },
  };
}

export default function Page() {
  // Server-render the explanatory copy (crawlable, link-worthy);
  // hydrate only the interactive widget. Keeps the asset fast + indexable.
  return (
    <article className="prose mx-auto max-w-3xl py-12">
      <h1>ROI Calculator</h1>
      <Calculator />
    </article>
  );
}

JSON-LD that makes original research citable (helps journalists and AI assistants attribute you):

// Inline in the asset page's RSC body
const jsonLd = {
  "@context": "https://schema.org",
  "@type": "Dataset",
  name: "2026 SaaS Onboarding Benchmark",
  description: "Survey of 1,200 B2B SaaS onboarding flows.",
  creator: { "@type": "Organization", name: "Your Org" },
  license: "https://creativecommons.org/licenses/by/4.0/",
  url: `${process.env.NEXT_PUBLIC_SITE_URL}/research/onboarding-2026`,
};
// <script type="application/ld+json" dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }} />

Protect earned equity on our stack:

• When a linked URL changes, add a 301 redirect in next.config (or middleware) so link equity transfers — never 404 a page that has backlinks.
• Reclaim links pointing at 404s: export referring URLs to dead pages, then 301 them to the nearest live equivalent.
• Keep canonicals stable; locale variants (next-intl) should canonical to the right localized URL so links to a campaign consolidate instead of splitting.

Output format

Backlink Health Score: XX/100   (or INSUFFICIENT DATA — Y/7 factors scored)

| Section                   | Status        | Score  | Source (confidence) |
|---------------------------|---------------|--------|---------------------|
| Profile overview          | pass/warn/fail| XX/100 | API (1.0)           |
| Anchor distribution       | pass/warn/fail| XX/100 | SC (0.85)           |
| Referring-domain quality  | pass/warn/fail| XX/100 | web-graph (0.5)     |
| Toxic links               | pass/warn/fail| XX/100 | API (1.0)           |
| Expired/heritage risk     | info          | N/A    | archive + API       |
| Parasite/negative exposure| pass/warn/fail| XX/100 | crawl (0.95)        |
| Link velocity & gap       | pass/warn/fail| XX/100 | API time-series     |

Critical (fix now) · High (≤1 month) · Medium (ongoing) · Link-building opportunities (top 10)

Do not duplicate other skills: send crawlability/redirect-mechanics deep-dives to seo-technical, E-E-A-T/content authority to seo-content, and data-source setup to seo-rank-data.

Parts adapted from claude-seo (MIT, © 2026 agricidaniel).